Programming Languages

 Discovering the Joy of Programming

    Building a program using Scratch was a delightful experience that felt more like playing a game than traditional programming. As I dragged and dropped colorful blocks to create animations and interactive stories, I quickly realized how intuitive the visual interface made coding. This hands-on approach allowed me to grasp fundamental programming concepts, such as loops and conditionals, in a playful way. I learned that programming is not just about writing lines of code, it's about problem-solving and creativity.

    Comparing my experience with Scratch to the activities in Section 10.1 of the textbook, I found that Scratch embodies the essence of interpreted languages. It allows for immediate feedback, which is quite different from compiled languages that require a more rigid, step-by-step approach before seeing results. While working with assembly languages felt daunting due to their complexity and low-level nature, I appreciated the power they hold for system-level programming. Query languages, like SQL, were straightforward but served a very different purpose for managing and retrieving data efficiently.

    Among the languages discussed, Scratch was by far the easiest for me to use due to its user-friendly interface and visual feedback. I can imagine Scratch being most effective in educational settings, where young learners can explore programming concepts without the alarming of syntax errors. On the other hand, I see compiled languages as ideal for building complex software applications that require development and experience. Assembly languages would be most effective in scenarios where hardware control and performance are critical, such as in set systems. Finally, query languages are invaluable for any application that involves large datasets, making data recovery straightforward and efficient.

Short Program: https://scratch.mit.edu/projects/1184020251/editor

 

References

Scott, M. L., & ProQuest (Firm). (2006). Programming language pragmatics [electronic resource] / Michael L. Scott. Morgan Kaufmann.

Erik Hombre Cuevas, Daniel Zaldivar, & Marco Perez. (2025). Impact of Programming Languages on Learning Performance. International Journal of Information and Communication Technology Education, 21(1). https://doi.org/10.4018/IJICTE.371419

Hill, C., Du, L., Johnson, M., & McCullough, B. D. (2024). Comparing programming languages for data analytics: Accuracy of estimation in Python and R. WIREs: Data Mining & Knowledge Discovery, 14(3), 1–21. https://doi.org/10.1002/widm.1531


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